Will the IGV Software ETF Continue to Be Hit by AI Budget Reallocation?

IGV may still continue to be affected by AI budget reallocation, but that does not mean the software industry has lost its long-term value. A more accurate view is that enterprise IT budgets are shifting away from traditional software subscriptions, IT services, and lower-priority SaaS projects toward servers, storage, memory, GPUs, cloud infrastructure, data governance, and cybersecurity. The real question is not whether “software will be replaced by AI,” but whether IGV’s holdings can turn AI demand into orders, renewals, margins, and free cash flow.

Key Takeaways

• The main pressure on IGV comes from the rising priority of AI infrastructure.
• Software ETFs are not homogeneous; cybersecurity and data platforms are more resilient.
• IBM’s budget reallocation signal amplified concerns around the software sector.
• Rising enterprise AI spending does not mean every SaaS company will benefit.
• To assess IGV, watch orders, renewal rates, margins, and AI monetization.
• Allocation decisions should compare IGV with QQQ, XLK, and AI hardware exposure.

Why Does AI Budget Reallocation Pressure the IGV Software ETF?

IGV is being pressured by AI budget reallocation mainly because enterprise IT budgets are not unlimited. When servers, storage, memory, GPUs, and cloud compute become short-term scarce resources, CIOs and CFOs tend to prioritize infrastructure, while some traditional software projects, underused SaaS subscriptions, and deferrable system upgrades are pushed down the priority list. IGV’s constituents are concentrated in software, systems software, cybersecurity, data platforms, and enterprise applications, which makes the ETF highly sensitive to enterprise software purchasing cycles.

“AI budget reallocation” does not mean companies have stopped buying software. It means budget priorities have changed. In the past, enterprises may have allocated budgets to CRM, collaboration tools, marketing automation, HR systems, data visualization, and cloud-native development tools. In the AI investment cycle, budgets are more likely to flow toward data centers, AI-optimized servers, cloud IaaS, memory, storage, and networking equipment. According to Gartner’s forecast for worldwide AI spending in 2026, AI spending is expected to grow 47% year over year, with AI-optimized IaaS, servers, networking, processing chips, and devices becoming the largest spending category, accounting for more than 45% of the total.

IBM’s warning intensified this concern. In an IBM investor letter, the company said that in the final weeks of June, customers shifted quarterly capex toward servers, storage, and memory purchases to secure infrastructure supply that was becoming constrained. Markets can interpret such language as an industry signal: if enterprises are redirecting budget from software to AI infrastructure, software companies’ order cycles, revenue growth, and valuation multiples may all come under pressure. The related IBM SEC filing also disclosed preliminary second-quarter financial data, further focusing market attention on whether enterprise software spending is slowing.

IGV is also sensitive because of its fund positioning. The iShares Expanded Tech-Software Sector ETF tracks North American software companies and some interactive media and services companies. It is not a single SaaS product, but a software risk basket. It includes application software, systems software, cybersecurity, data platforms, and some digital platform companies. In other words, IGV will not lose value across the board simply because traditional SaaS is under pressure, but it is affected by overall software-sector sentiment.

You also need to distinguish between “budget crowd-out” and “demand disappearance.” AI infrastructure may crowd out software budgets in the short term, but that does not mean software becomes unimportant over the long term. After enterprises buy compute capacity, they still need data governance, identity security, model deployment, workflow automation, observability tools, and industry applications to capture AI value. IGV’s pressure comes from this middle phase: hardware and data centers receive budget first, while software revenue recognition, AI feature pricing, and enterprise workflow transformation take longer to materialize.

Summary: IGV is being hit by AI budget reallocation not because demand for software has disappeared, but because enterprise IT budgets are being reprioritized between AI infrastructure and software subscriptions. Servers, storage, memory, and cloud compute are more urgent in the short term, so traditional software projects are easier to delay. However, cybersecurity, data platforms, observability tools, and AI workflow software may still benefit. The key to assessing IGV is not simply asking whether “software will be replaced by AI,” but whether the ETF’s holdings can enter the enterprise AI production chain and translate AI demand into verifiable revenue, margins, and free cash flow.

How Does IGV’s Holdings Structure Determine Which Software Stocks Are More Vulnerable?

Whether IGV continues to face pressure depends on which of its top holdings are viewed as AI beneficiaries and which are viewed as victims of traditional software budget cuts. Cybersecurity, data platforms, systems software, and AI workflow companies are more likely to be resilient. Application software companies with low growth, slowing seat expansion, and weak pricing power are more vulnerable. You should not treat IGV simply as a “traditional SaaS ETF.” It is better understood as a concentrated expression of structural divergence within the software sector.

According to IGV’s latest holdings, the fund includes companies such as Palo Alto Networks, Palantir, Microsoft, CrowdStrike, Oracle, Salesforce, ServiceNow, AppLovin, Fortinet, and Adobe. This mix gives IGV three types of exposure: defensive AI-related demand in cybersecurity and data platforms, systems software and cloud platform exposure through companies such as Microsoft and Oracle, and budget-sensitive enterprise application software through companies such as Salesforce and Adobe.

The software categories most vulnerable to AI budget reallocation are usually not all software companies, but those with low differentiation, low utilization, and hard-to-prove ROI. When budgets tighten, enterprises reassess seat-based pricing, duplicate tools, overlapping functions, and underused subscriptions. Marketing automation, collaboration tools, non-core back-office software, project-based system upgrades, and deferrable application purchases are often easier to delay or reduce. If a software company can only tell an AI story without proving that AI features drive higher ARPU, better renewals, or customer expansion, valuation pressure becomes more obvious.

The more resilient companies usually share three characteristics. The first group is cybersecurity. AI-driven attacks, identity risk, cloud security, and endpoint protection make security budgets harder to cut. The second group is data platforms and observability tools. To bring AI into production, enterprises need to clean data, monitor systems, manage models, and track costs. The third group is core workflow and systems software. If a product is already deeply embedded in enterprise operations, customers cannot easily cancel the subscription.

The market has also started to shift from “all software is hurt” to “which companies can prove AI monetization.” Morgan Stanley’s view on AI disruption risks for software stocks suggests that some software and data stocks may have been excessively punished by AI replacement fears. Market discussions have also pointed to cybersecurity, Snowflake, ServiceNow, and Datadog as areas that may benefit from the AI investment cycle and enterprise AI workload preparation. This does not mean all software stocks will rebound; it means capital will become more selective.

Therefore, IGV’s risk is not “owning software” in itself, but whether its high-weight holdings can survive the budget reprioritization cycle. If security, data, workflow, and systems software among the top holdings outperform application software, IGV may enter a choppy recovery. If high-weight enterprise application software names continue to lower guidance, the fund may still lag QQQ, XLK, or semiconductor ETFs.

Summary: IGV’s holdings structure means it should not be simplistically classified as a “traditional SaaS victim.” The fund includes application software that may be affected by delayed enterprise budgets, but it also includes companies that may benefit from AI security, data governance, workflow automation, and systems software upgrades. The real distinction is software type: low-differentiation, low-utilization, hard-to-prove-ROI software is more fragile; security, data, observability, AI workflow, and core systems software are more likely to remain budget priorities. IGV’s future performance will depend heavily on the weight and execution quality of these categories.

Is AI Infrastructure Crowding Out Software a Short-Term Disruption or a Long-Term Trend?

In the short term, AI infrastructure is genuinely crowding out software budgets, especially when servers, memory, storage, and GPUs are in tight supply and companies expect prices to rise. Enterprises are more likely to secure hardware resources early. Over the long term, however, AI infrastructure still needs software, data, security, and workflows to convert compute into productivity. IGV’s pressure is more like a mismatch between investment phases, not a permanent disappearance of software demand.

The short-term pressure comes from annual budgets and purchasing windows. Enterprise IT spending is often set on a yearly basis, while AI infrastructure faces supply-chain constraints. When data center resources, AI chips, memory, and storage are expected to become more expensive or harder to secure, companies allocate budget to infrastructure earlier. According to Gartner’s forecast for worldwide IT spending in 2026, global IT spending is expected to reach $6.31 trillion, up 13.5%, driven by AI infrastructure, software, and IaaS. The issue is that overall IT spending growth does not mean every software company benefits at the same time; internal budget prioritization matters more.

Over the medium to long term, software will not disappear, but the valuation logic will change. In the past, the core SaaS story focused on subscription revenue, net revenue retention, seat expansion, and gross margins. In the AI era, the key questions will include whether AI improves customer efficiency, whether AI features can be priced separately, whether inference costs erode margins, and whether customers are willing to entrust core workflows to software vendors. In other words, software companies cannot simply say they have AI features. They must prove that AI drives higher usage, stronger renewals, higher ARPU, or better free cash flow margins.

Enterprise software “build versus buy” decisions may also change. Research on agentic AI and enterprise software build-versus-buy decisions argues that the “SaaSocalypse” narrative may be overstated for many enterprise application categories. AI is more likely to shift the buy-versus-build boundary across software categories: generic tools and differentiated internal applications may be more suitable for in-house development, while regulated, mission-critical systems and complex enterprise workflows are more likely to continue relying on mature software vendors. This matters for IGV because the fund contains both applications that may face build-in-house pressure and security, governance, and core systems software that is much harder to replace.

This process can be understood in three stages. In the first stage, hardware and infrastructure capture the largest share of incremental budget, putting pressure on software ETFs. In the second stage, enterprises begin piloting AI applications and need data platforms, security, observability, access control, and workflow automation; this is when IGV begins to diverge internally. In the third stage, if AI truly enters business processes, high-quality software companies with industry data, workflow entry points, and customer stickiness may regain valuation premiums. Whether IGV can move from the first stage to the third depends on how quickly its holdings convert AI into revenue.

Summary: In 2026, AI infrastructure crowding out software budgets looks like a combination of real short-term pressure and long-term structural revaluation. In the short term, enterprises are prioritizing servers, storage, memory, and cloud compute, causing IGV to come under pressure as software growth expectations are revised lower. Over the long term, if AI truly enters production workflows, software, data, security, and workflow tools remain essential for converting compute into business value. IGV’s problem is not whether software has a future, but which holdings can evolve from “selling subscriptions” to “selling AI productivity” and prove that with financial data.

What Earnings and Market Signals Show Whether IGV Has Bottomed?

Whether IGV has bottomed should not be judged only by a technical rebound. You need to watch whether software earnings expectations have stopped being revised down, whether orders are recovering, whether AI features are producing measurable revenue, and whether valuations have returned to reasonable levels. If the rebound is driven only by sentiment while earnings still show slowing renewals, reduced seat counts, longer sales cycles, and deteriorating free cash flow, IGV may still face another wave of pressure. A price bottom, valuation bottom, and fundamental bottom are not the same thing.

There has already been discussion that software stocks are stabilizing. MarketWatch’s observation on the software sector noted that IGV had fallen nearly 40% from its September 2025 high to its April 2026 low, before software stocks and related debt markets showed some signs of stabilization. This suggests sentiment may have become overly negative, but it does not by itself prove that fundamentals have bottomed. The key question is whether subsequent earnings stop being revised downward.

To judge whether IGV has bottomed, separate the process into three layers. A sentiment bottom means bad news is largely priced in and software stocks no longer drop sharply on negative headlines. A valuation bottom means P/S, EV/FCF, and P/E have returned to levels that can be supported by growth quality. A fundamental bottom means ARR, RPO, billings, renewal rates, net revenue retention, margins, and free cash flow margins have stopped worsening. Only when all three layers improve together does IGV’s rebound become more reliable.

In constituent earnings reports, five groups of indicators matter most. The first is forward revenue indicators, including ARR, RPO, billings, and remaining performance obligations. The second is customer quality indicators, including renewal rates, net revenue retention, and large-customer expansion. The third is AI monetization indicators, including separately priced AI features, AI customer penetration, and upsell. The fourth is cost indicators, including inference costs, cloud costs, and gross margins. The fifth is shareholder-quality indicators, including free cash flow margin, stock-based compensation as a percentage of revenue, and whether buybacks offset dilution.

You should also watch for a “rebound trap.” Software stock rebounds may come from short covering, lower interest rates, analyst upgrades, oversold recovery, or renewed AI concept trading. But if more companies lower full-year guidance, customer purchasing cycles continue to lengthen, AI features fail to support pricing, cloud costs compress gross margins, or high-valuation software companies miss expectations, IGV can remain under pressure. IGV is an ETF, so it is not exposed to one company’s earnings in the same way a single stock is, but concentrated weakness among top holdings can still affect fund performance.

Summary: To judge whether IGV has bottomed, do not focus only on how much it has rebounded from the low. The more important question is whether software companies’ earnings prove that enterprise budgets are no longer shifting away from software into hardware and infrastructure, and whether AI features are truly improving paid adoption, renewals, and margins. If revenue expectations, order quality, and free cash flow margins stabilize together, IGV’s pressure may ease. If the move is only a sentiment rebound while fundamentals are still being revised downward, the software ETF may continue to lag AI hardware, semiconductors, and broader technology ETFs.

How Should You Compare IGV, QQQ, XLK, and AI Hardware Stocks?

IGV is better suited for expressing a software-sector rebound and enterprise software re-rating than for representing the full AI investment opportunity. If you are bullish on continued AI infrastructure expansion, semiconductors, servers, data centers, and AI hardware supply chains offer more direct exposure. If you want broader exposure to large technology platforms, QQQ or XLK is broader. If you believe software sentiment has become too pessimistic, IGV is the more targeted vehicle. Different ETFs represent different AI narratives.

IGV’s core exposure is software, cybersecurity, data platforms, systems software, and enterprise applications. QQQ is more tilted toward large Nasdaq technology and growth stocks and is heavily influenced by mega-cap technology companies. XLK is more concentrated in large U.S. information technology companies, with higher exposure to platform stocks and semiconductors. Semiconductor ETFs provide more direct exposure to AI chips, equipment, packaging, servers, and data center capex. You should first decide whether you are more bullish on AI infrastructure or the AI application layer, and then choose the right instrument.

Before allocating to IGV, you need to clarify three views. First, has AI budget reallocation already been fully priced in? If IGV has fallen sharply but earnings expectations are still being revised down, the rebound may not be stable. Second, are you more bullish on infrastructure or the application layer? The infrastructure thesis is more linked to chips, servers, and data centers, while the application-layer thesis is more linked to software, data, security, and workflows. Third, can you tolerate software-stock volatility? IGV’s risk-return profile differs from broad-market ETFs, and software-sector sentiment can amplify short-term volatility.

Trading costs also matter. ETF investing is not just about the fund expense ratio. You also need to consider commissions, platform fees, external agency fees, bid-ask spreads, FX costs, and order execution. IGV’s own expense ratio can be checked in the iShares IGV fund profile, but investors’ actual costs also depend on the trading platform, order type, and execution price. If you are watching trading opportunities in U.S. ETFs such as IGV, QQQ, and XLK, you should include actual trading costs in your net-return calculation.

If the relevant services are available in your region, you can use Biya to follow multi-asset market data across U.S. stocks, Hong Kong stocks, and cryptocurrencies. Biya charges $0 commission for U.S. stock trading, while platform fees, external agency fees, and other charges are subject to the U.S. stock trading fees and the order confirmation page. Service availability depends on your location, identity verification results, platform rules, and applicable laws and regulations. Before trading, you should fully understand fund holdings, bid-ask spreads, fee structure, FX impact, and your own risk tolerance.

Summary: IGV is not a complete AI investment tool; it is a risk asset focused more on the software layer. If you believe AI infrastructure remains the main theme, semiconductors and data center supply chains offer more direct exposure. If you want more diversified technology exposure, QQQ or XLK may be more suitable. If you believe software stocks have been overly punished by AI budget reallocation, IGV is a more targeted way to express that rebound view. Before allocating, compare industry logic, holdings structure, valuation, volatility, and trading costs rather than making a decision based only on short-term price moves.

Three Scenarios for the Future Path of the IGV Software ETF

IGV does not have a single future path. If enterprises continue prioritizing servers, storage, memory, GPUs, and cloud infrastructure while traditional software orders, renewals, and seat expansion slow, IGV may continue to lag semiconductor, data center, and broad technology ETFs. If enterprises start shifting AI investment toward application deployment, cybersecurity, data platforms, and workflow software may recover first. If the AI application layer truly takes over from infrastructure, IGV may regain a valuation premium.

The first scenario is continued pressure. Triggers include IBM-like warnings appearing at more software companies, SaaS companies lowering full-year revenue guidance, AI features failing to support standalone pricing, customer sales cycles continuing to lengthen, and earnings expectations for high-valuation software stocks being revised lower. In this scenario, IGV’s P/S, EV/FCF, and forward P/E multiples continue to compress, while capital remains more willing to chase AI hardware, semiconductors, and large platform stocks.

The second scenario is a choppy recovery. Cybersecurity, data platforms, observability tools, and enterprise workflow software outperform traditional application software. Enterprise AI projects move from pilot phase into deployment. Software companies begin showing AI upsell. Low-quality SaaS names are eliminated, and industry leaders gain share. Under this scenario, IGV may not rally sharply, but AI-related software among its top holdings can support fund performance, and the market shifts from “all software is hurt” to “select the AI software winners.”

The third scenario is renewed valuation premium. If enterprises finish the infrastructure buildout phase and begin large-scale deployment of data governance, security compliance, workflow automation, and industry application software, IGV’s narrative can shift from budget victim to application-layer beneficiary. Triggers include AI features raising ARPU, inference costs not significantly eroding gross margins, renewal rates recovering, net revenue retention improving, free cash flow margins rising, and the rate environment supporting growth-stock valuations.

For investors, the most practical tracking method is not chasing every AI headline, but reviewing three questions every earnings season: have revenue expectations for IGV’s top holdings stopped being revised lower? Are AI features generating real paid adoption rather than only appearing in product launches? Are free cash flow margins stable rather than being consumed by inference costs, sales expenses, and stock-based compensation? If these three answers gradually turn positive, IGV’s pressure may ease. If they continue to worsen, the rebound is more likely to be a trading bounce.

Summary: IGV does not have a single future path. If AI infrastructure continues absorbing enterprise budgets, software stocks may remain under pressure. If enterprises begin converting compute into data governance, security, workflow, and application deployment, internal divergence within IGV should appear first. If the AI application layer truly takes over from infrastructure, IGV may regain a valuation premium. The most important tracking indicators are not news headlines, but software-company orders, renewals, AI revenue, margins, and free cash flow. You need to analyze IGV through scenarios rather than using a single price move to judge the outlook for software.

Tracking IGV requires more than a directional view. You also need real-time prices, holdings, fees, and risk data. Software ETF valuations can adjust quickly as constituent earnings, enterprise IT spending, AI infrastructure cycles, and interest-rate expectations change. You can use U.S. stock information lookup to track basic information on IGV, QQQ, XLK, Microsoft, Oracle, Palo Alto Networks, CrowdStrike, and other U.S. stocks and ETFs, and you can download the App to follow related market updates. This content introduces only public market information, industry logic, and fee structures, and does not constitute investment advice. Before trading, review fund documents, order confirmations, fee details, FX costs, and locally applicable rules.

FAQ

What Software Companies Does the IGV ETF Mainly Hold?

IGV mainly holds North American software companies and some interactive media companies. Its top holdings often include Palo Alto Networks, Palantir, Microsoft, CrowdStrike, Oracle, Salesforce, ServiceNow, AppLovin, Fortinet, and Adobe. Actual holdings may change with fund adjustments, price movements, and index rules, so investors should rely on the latest fund disclosure.

Why Does AI Budget Reallocation Pressure IGV?

AI budget reallocation pressures IGV because enterprises are prioritizing servers, storage, memory, GPUs, and cloud infrastructure in the short term, causing some software projects to be delayed or reduced. The largest impact is on software companies with hard-to-prove ROI, low utilization, slowing seat growth, or weaker pricing power.

Is IGV or QQQ Better for Investors Bullish on the AI Application Layer?

If you are more bullish on software, data, security, and enterprise AI applications, IGV offers more concentrated industry exposure. If you want broader exposure that includes large technology platforms, semiconductors, and growth stocks, QQQ is more diversified. Their risk sources are different, so allocation should not be decided only by short-term performance.

Does IGV’s Decline Mean AI Is Replacing the Software Industry?

IGV’s decline does not mean AI is replacing the software industry. It more likely reflects changing enterprise budget priorities and valuation re-rating. Cybersecurity, data platforms, observability tools, and AI workflow software may still benefit, while low-differentiation traditional SaaS faces greater pressure.

What Risks Should Beginners Consider Before Investing in IGV?

Beginners should consider software-stock valuation volatility, constituent concentration, AI budget crowd-out, fund expenses, bid-ask spreads, and FX costs before investing in IGV. They should also confirm their own risk tolerance and refer to fund documents, order pages, and local regulatory requirements.

Can IGV Replace Investing in Individual Software Stocks?

IGV can reduce single-company earnings risk, but it cannot eliminate overall software-sector risk. It is more suitable for expressing a view on software-sector recovery or leading subsector rebound. If you have a strong view on one company’s fundamentals, an individual stock may offer greater upside potential, but it also carries higher volatility.